Detection Methods

DataLeakTest

Updated 5/17/2021

DLP Validation & Testing

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Detection Methods

When to use them and what they will do for you

Maturity	Methods [of Data Detection]	Policy to Business Mapping	Risk Reduction	Typical Accuracy/ False positive
Phase I: Monitoring	File Properties [type, size, age] Key words, Patterns, dictionaries OCR (Optical Character Recognition) or a more modern term GTA (Graphical Text Analysis)	Discovering business processes Early blocking of damaging destinations Data use discovery Data transfer method Discovery Drip DLP monitoring	20%	80/20
Phase II: Notifications & End user Education	Regular Expressions Lexical analysis Statistical analysis File Tagging OCR (Optical Character Recognition) or a more modern term GTA (Graphical Text Analysis)	end user notifications Continued blocking of damaging destinations Destination Awareness Data Source Discovery Data use discovery Data transfer method Control Intro to "Drip DLP" control	50%	90/10
Phase III: Blocking & Control	File hashing/ Fingerprinting Database record hashing/ fingerprinting Multi-accuracy/ blended policies OCR (Optical Character Recognition) or a more modern term GTA (Graphical Text Analysis) Machine learning	End user Education Blocking of bad business processes Source and Destination Control Data Destination Control Data transfer method control Data use control Data Source Control Advanced "Drip DLP" control	80%+	95+/5-

-Basic pattern matching will get you %20-%40 accuracy out of the box. Refinement to business practices and destination awareness will bring that accuracy up to the 80% mark.

-Pattern matching with lexical (word relation), statistical analysis (likelihood measurement), advanced positive and negative dictionaries, and data validation (ex. luhn check for credit cards, US Social Security number checked against the Social Security Administrations list of valid SS#'s) will get you %40-%60 OOB %80 once refined *Look for a product with out of the box policies around Federal and Industry regulations. These policies should cover things like multi language support including Chinese double-byte character recognition

Blended Policy Approach to Data Security: As you model your business and define how data is used, make it a point to use at least 2 policy levels;

Base Policies -catch interesting events, items that you wouldn't want to raise alarms over because its catching many uninteresting items. This data captured will be used in investigations or "Drip DLP"
Critical Event Policies -these are very accurate policies usually developed in Phase II or III.

By context awareness or destination awareness means the ability to look at the destination of your data and make some really easy decisions. Botnets and keyloggers are a great example. Regardless of the data why would you let it go to a keylogger or botnet? That should be a transaction you can immediately block without stopping business. Instantly lowering Data risk, drastically increasing security posture, with out the risk of breaking a business process. Knowing the context of the data becomes key to implementing Data Security. *Look for a Data Security tool that integrates closely with a Web Security/ malware tool.